Focus Issue on Roots: Beyond the Barrier: Communication in the Root through the Endodermis

The root endodermis is characterized by the Casparian strip and by the suberin lamellae, two hydrophobic barriers that restrict the free diffusion of molecules between the inner cell layers of the root and the outer environment. The presence of these barriers and the position of the endodermis between the inner and outer parts of the root require that communication between these two domains acts through the endodermis. Recent work on hormone signaling, propagation of calcium waves, and plant-fungal symbiosis has provided evidence in support of the hypothesis that the endodermis acts as a signaling center. The endodermis is also a unique mechanical barrier to organogenesis, which must be overcome through chemical and mechanical cross talk between cell layers to allow for development of new lateral organs while maintaining its barrier functions. In this review, we discuss recent findings regarding these two important aspects of the endodermis.Soil contains water and dissolved nutrients needed for plant growth, but also holds pathogens and toxic compounds that can be detrimental to the plant. The root system, which is directly in contact with soil particles, can integrate environmental cues to adjust its development in order to optimize nutrient (Péret et al., 2011; Lynch, 2013) and water uptake (Cassab et al., 2013; Lynch, 2013; Bao et al., 2014) or avoid regions of high salinity (Galvan-Ampudia et al., 2013). Once anchored in the soil, roots must deal with the constraints of their local environment and develop specific barriers to balance uptake of nutrients, water, and interactions with symbionts with protection against detrimental biotic and abiotic factors.In young roots, these barriers are mainly formed by the deposition of hydrophobic polymers such as lignin and suberin within the primary cell wall of the endodermis, which separates the pericycle from the cortex (Fig. 1), and of the exodermis, which lies between the cortex and the epidermis (Nawrath et al., 2013). Although formation of an exodermis is species dependent, the endodermis is a distinguishing figure of extant vascular plants (Raven and Edwards, 2001). Within this layer, two barriers (i.e. the Casparian strip and the suberin lamellae) are sequentially deposited and regulate water and nutrient movements between the inner and outer parts of the root. In this review, we discuss how the presence of these two major endodermal barriers affects communication between the different cell layers of the root. We focus on recent articles highlighting the importance of the endodermis in this communication during various biological and developmental processes.Open in a separate windowFigure 1.Endodermal barriers affect radial movement of water and solutes through the root. A, At the root tip, to move from the soil to the outer tissues of the root and then into the stele, water and solute molecules can use either the apoplastic (black lines), symplastic (dotted lines), or transcellular (dashed lines) pathways. B, The deposition of the Casparian strip in the endodermis prevents the free apoplastic diffusion of molecules between the outer part and the inner part of the root forcing molecules to pass through the symplast of endodermal cells. C, The deposition of suberin lamellae prevents the uptake of molecules from the apoplast directly into the endodermis forcing molecules to enter the symplast from more outer tissue layers. Suberin deposition is also likely to prevent the backflow of water and ions out of the stele. Passage cells are unsuberized and may facilitate the uptake of water and nutrients in older parts of the root. Cor, Cortex; End, endodermis; Epi, epidermis; Peri, pericycle; Vasc, vasculature. Figure redrawn and modified from Geldner et al. (2013).     

Focus Issue on Plant Cell Walls: Sequencing around 5-Hydroxyconiferyl Alcohol-Derived Units in Caffeic Acid O-Methyltransferase-Deficient Poplar Lignins

Caffeic acid O-methyltransferase (COMT) is a bifunctional enzyme that methylates the 5- and 3-hydroxyl positions on the aromatic ring of monolignol precursors, with a preference for 5-hydroxyconiferaldehyde, on the way to producing sinapyl alcohol. Lignins in COMT-deficient plants contain benzodioxane substructures due to the incorporation of 5-hydroxyconiferyl alcohol (5-OH-CA), as a monomer, into the lignin polymer. The derivatization followed by reductive cleavage method can be used to detect and determine benzodioxane structures because of their total survival under this degradation method. Moreover, partial sequencing information for 5-OH-CA incorporation into lignin can be derived from detection or isolation and structural analysis of the resulting benzodioxane products. Results from a modified derivatization followed by reductive cleavage analysis of COMT-deficient lignins provide evidence that 5-OH-CA cross couples (at its β-position) with syringyl and guaiacyl units (at their O-4-positions) in the growing lignin polymer and then either coniferyl or sinapyl alcohol, or another 5-hydroxyconiferyl monomer, adds to the resulting 5-hydroxyguaiacyl terminus, producing the benzodioxane. This new terminus may also become etherified by coupling with further monolignols, incorporating the 5-OH-CA integrally into the lignin structure.Lignins are polymeric aromatic constituents of plant cell walls, constituting about 15% to 35% of the dry mass (Freudenberg and Neish, 1968; Adler, 1977). Unlike other natural polymers such as cellulose or proteins, which have labile linkages (glycosides and peptides) between their building units, lignins’ building units are combinatorially linked with strong ether and carbon-carbon bonds (Sarkanen and Ludwig, 1971; Harkin, 1973). It is difficult to completely degrade lignins. Lignins are traditionally considered to be dehydrogenative polymers derived from three monolignols, p-coumaryl alcohol 1h (which is typically minor), coniferyl alcohol 1g, and sinapyl alcohol 1s (Fig. 1; Sarkanen, 1971). They can vary greatly in their composition in terms of their plant and tissue origins (Campbell and Sederoff, 1996). This variability is probably determined and regulated by different activities and substrate specificities of the monolignol biosynthetic enzymes from different sources, and by the carefully controlled supply of monomers to the lignifying zone (Sederoff and Chang, 1991).Open in a separate windowFigure 1.The monolignols 1, and marker compounds 2 to 4 resulting from incorporation of novel monomer 15h into lignins: thioacidolysis monomeric marker 2, dimers 3, and DFRC dimeric markers 4.Recently there has been considerable interest in genetic modification of lignins with the goal of improving the utilization of lignocellulosics in various agricultural and industrial processes (Baucher et al., 2003; Boerjan et al., 2003a, 2003b). Studies on mutant and transgenic plants with altered monolignol biosynthesis have suggested that plants have a high level of metabolic plasticity in the formation of their lignins (Sederoff et al., 1999; Ralph et al., 2004). Lignins in angiosperm plants with depressed caffeic acid O-methyltransferase (COMT) were found to derive from significant amounts of 5-hydroxyconiferyl alcohol (5-OH-CA) monomers 15h (Fig. 1) substituting for the traditional monomer, sinapyl alcohol 1s (Marita et al., 2001; Ralph et al., 2001a, 2001b; Jouanin et al., 2004; Morreel et al., 2004b). NMR analysis of a ligqnin from COMT-deficient poplar (Populus spp.) has revealed that novel benzodioxane structures are formed through β-O-4 coupling of a monolignol with 5-hydroxyguaiacyl units (resulting from coupling of 5-OH-CA), followed by internal trapping of the resultant quinone methide by the phenolic 5-hydroxyl (Ralph et al., 2001a). When the lignin was subjected to thioacidolysis, a novel 5-hydroxyguaiacyl monomer 2 (Fig. 1) was found in addition to the normal guaiacyl and syringyl thioacidolysis monomers (Jouanin et al., 2000). Also, a new compound 3g (Fig. 1) was found in the dimeric products from thioacidolysis followed by Raney nickel desulfurization (Lapierre et al., 2001; Goujon et al., 2003).Further study with the lignin using the derivatization followed by reductive cleavage (DFRC) method also confirmed the existence of benzodioxane structures, with compounds 4 (Fig. 1) being identified following synthesis of the authentic parent compounds 9 (Fig. 2). However, no 5-hydroxyguaiacyl monomer could be detected in the DFRC products. These facts imply that the DFRC method leaves the benzodioxane structures fully intact, suggesting that the method might therefore be useful as an analytical tool for determining benzodioxane structures that are linked by β-O-4 ethers. Using a modified DFRC procedure, we report here on results that provide further evidence for the existence of benzodioxane structures in lignins from COMT-deficient plants, that 5-OH-CA is behaving as a rather ideal monolignol that can be integrated into plant lignins, and demonstrate the usefulness of the DFRC method for determining these benzodioxane structures.Open in a separate windowFigure 2.Synthesis of benzodioxane DFRC products 12 (see later in Fig. 6 for their structures). i, NaH, THF. ii, Pyrrolidine. iii, 1g or 1s, benzene/acetone (4/1, v/v). iv, DIBAL-H, toluene. v, Iodomethane-K₂CO₃, acetone. vi, Ac₂O pyridine.     

Unanticipated Success Stories: An Interview with Angelika Amon

THE Genetics Society of America Medal is awarded to an individual for outstanding contributions to the field of genetics in the past 15 years. Recipients of the GSA Medal are recognized for elegant and highly meaningful contributions to modern genetics. The 2014 recipient, Angelika B. Amon, has uncovered key principles governing the cell cycle and was the first to demonstrate a connection between the physical completion of anaphase and the initiation of mitotic exit. More recently, her research has focused on the consequences of aneuploidy. GENETICS spoke with Dr. Amon about her approach to science and what is next on the horizon.Open in a separate windowAngelika B. Amon     

Chlorophyll f-driven photosynthesis in a cavernous cyanobacterium

Chlorophyll (Chl) f is the most recently discovered chlorophyll and has only been found in cyanobacteria from wet environments. Although its structure and biophysical properties are resolved, the importance of Chl f as an accessory pigment in photosynthesis remains unresolved. We found Chl f in a cyanobacterium enriched from a cavernous environment and report the first example of Chl f-supported oxygenic photosynthesis in cyanobacteria from such habitats. Pigment extraction, hyperspectral microscopy and transmission electron microscopy demonstrated the presence of Chl a and f in unicellular cyanobacteria found in enrichment cultures. Amplicon sequencing indicated that all oxygenic phototrophs were related to KC1, a Chl f-containing cyanobacterium previously isolated from an aquatic environment. Microsensor measurements on aggregates demonstrated oxygenic photosynthesis at 742 nm and less efficient photosynthesis under 768- and 777-nm light probably because of diminished overlap with the absorption spectrum of Chl f and other far-red absorbing pigments. Our findings suggest the importance of Chl f-containing cyanobacteria in terrestrial habitats.The textbook concept that oxygenic phototrophs primarily use radiation in the visible range (400–700 nm) has been challenged by several findings of unique cyanobacteria and chlorophylls (Chl) over the past two decades (Miyashita et al., 1996; Chen et al., 2010; Croce and van Amerongen, 2014) Unicellular cyanobacteria in the genus Acaryochloris primarily employ Chl d for oxygenic photosynthesis at 700–720 nm (Miyashita et al., 1996) and thrive in shaded habitats with low levels of visible light but replete of near-infrared radiation (NIR, >700 nm, Kühl et al., 2005; Behrendt et al., 2011, 2012). Furthermore, Chl f was recently discovered in filamentous (Chen et al., 2010; Airs et al., 2014; Gan et al., 2014) and unicellular cyanobacteria (Miyashita et al., 2014), enabling light harvesting even further into the NIR region up to ∼740 nm, often aided by employing additional far-red light-absorbing pigments such as Chl d and phycobiliproteins (Gan et al., 2014). Whereas the biochemical structure (Willows et al., 2013) and biophysical properties (Li et al., 2013; Tomo et al., 2014) of Chl f have been studied in detail, the actual importance of this new chlorophyll for photosynthesis is hardly explored (Li et al., 2014).Chlorophyll f has been found in cyanobacteria originating from aquatic/wet environments: the filamentous Halomicronema hongdechloris from stromatolites in Australia (Chen et al., 2012), a unicellar morphotype (Strain KC1) from Lake Biwa in Japan (Akutsu et al., 2011; Miyashita et al., 2014) and a filamentous Leptolyngbya sp. strain (JSC-1, Gan et al., 2014) from a hot-spring and in a unicellular Chlorogloeopsis fritschii strain from rice paddies (Airs et al., 2014). In this study, we report on a unicellular Chl f-containing cyanobacterium originating from a wet cavernous habitat and demonstrate its capability of NIR-driven oxygenic photosynthesis. Enrichments of the new cyanobacterium were obtained from a dense dark green-blackish biofilm dominated by globular morphotypes of Nostocaceae growing on moist limestone outside Jenolan Caves, NSW, Australia. The sampling site was heavily shaded even during mid-day with low irradiance levels of 400- to 700-nm light varying from 0.5 to 5 μmol photons m⁻² s⁻¹. Biofilms were carefully scraped off the substratum and kept in shaded zip-lock bags in a moist atmosphere until further processing. Samples were then incubated at 28 °C in a f/2 medium under NIR at 720 nm (∼10 μmol photons m⁻² s⁻¹) yielding conspicuous green cell aggregates after several months of incubation. Repeated transfer of the aggregates into fresh medium resulted in a culture predominated by green cell clusters (Figure 1a), exhibiting orange-red fluorescence upon excitation with blue light (Figure 1b). Transmission electron microscopy revealed that the green clusters consisted of slightly elongated unicellular cyanobacteria (∼1- to 2-μm wide and ∼2- to 3-μm long), with stacked thylakoids and embedded in a joint polymer matrix (Figure 1c). Hyperspectral microscopy (Kühl and Polerecky, 2008) of the clusters revealed distinct troughs in the transmission spectra at absorption maxima indicative of Chl a (675–680 nm) and Chl f (∼720 nm; Figure 1d, red line). In situ spectral irradiance measurements at the sampling site showed strong depletion of visible wavelengths in the 480- to 710-nm range (Figure 1d, gray line), whereas highest light levels were found in the near-infrared region of the solar spectrum at 710–900 nm. The presence of Chl a and f was further confirmed in enrichment cultures using high-performance liquid chromatography-based pigment analysis (Figure 1e, Supplementary Figure S1), while no Chl d was detected. In addition, weak spectral signatures of carotenoids and phycobilins, with absorption occurring at ∼495 and 665 nm, were evident in the hyperspectral data. Cyanobacteria, including those producing Chl d/f, are known to actively remodel their pigment content in response to the available light spectrum (Stomp et al., 2007; Chen and Scheer, 2013; Gan et al., 2014) and Chl d/f has almost exclusively been found in cyanobacteria grown under far-red light and not under visible light (Kühl et al., 2005; Chen et al., 2010; Airs et al., 2014; Gan et al., 2014; Li et al., 2014; Miyashita et al., 2014). Recent work describes this acclimation response as ‘Far-Red Light photoacclimation'' (FaRLiP), which, in strain JSC-1, comprises a global change in gene expression and structural remodeling of the PSII/PSI core proteins and phycobilisome constituents (Gan et al., 2014). The extent to which this arrangement results in optimized photosynthetic performance is only known for the NIR (=710 nm)-acclimated strain JSC-1, where exposure to wavelengths >695 nm resulted in 40% higher O₂ evolution rates as compared with cells that were previously adapted to red light (645 nm; Gan et al., 2014). Yet the discrimination of actinic wavelengths and their relative effect on gross photosynthesis in Chl f-containing cells needs further investigation. Using an O₂ microsensor and the light–dark shift method (Revsbech et al., 1983) on embedded Chl f-containing aggregates, we found maximal gross photosynthesis rates (∼1.06 μmol O₂ cm⁻³ s⁻¹) to occur at irradiances of ∼250 μmol photons m⁻² s⁻¹ of 742 nm (half-bandwidth, HBW, 25 nm, Figures 2a and b) with light saturation to occur very early at ∼35 μmol photons m⁻² s⁻¹. Further red-shifted actinic light, that is, 768 nm (HBW 28 nm) and 777 nm (HBW 30 nm), yielded lower O₂ evolution rates, which, in all likelihood, are an effect of the diminished overlap with far-red light-absorbing pigments, including Chl f (Figures 2a and b). As O₂ evolution rates were measured on non-axenic cell aggregates, 16S rDNA amplicon sequencing was employed to determine the microbial diversity found within the enrichment culture. This revealed the presence of a variety of bacterial types, including anoxygenic phototrophs, yet all sequences for known oxygenic phototrophs in the data set (∼9.3% of all reads on the order level, Supplementary Figure S2) formed a single operational taxonomic unit (OTU) closely affiliated with the Chl f-containing strain KC1 (Miyashita et al., 2014, Figure 2c).Open in a separate windowFigure 1Imaging and pigment analysis of Chl f-containing cyanobacteria isolated from a cavernous low-light environment. (a) Representative bright field microscope image of cultured cells grown under 720 nm NIR. (b) Fluorescence image of the same cells as in a, excited at 450–490 nm, with emission being detected at >510 nm. (c) Transmission electron microscopy of a Chl f-containing cyanobacterium with densely stacked thylakoid membranes. (d) Transmittance spectrum of cell aggregate determined by hyperspectral imaging (red line). Ambient light conditions at the site of isolation (gray line), as measured by a spectroradiometer. Note the Chl f-specific in vivo absorption at ∼720 nm in the transmittance spectrum (dotted line). Small insert picture denotes the cells and area of interest (black arrow) from which the spectrum was taken. (e) In vitro absorption spectrum of Chl f extracted from enrichment cultures and analyzed via high-performance liquid chromatography. The two Chl f-specific absorption peaks (404 and 704 nm in acetone:MeOH solvent) are indicated.Open in a separate windowFigure 2Taxonomic affiliation and O₂ evolution of Chl f-containing cells as determined by O₂ microelectrode measurements and 16 S rDNA amplicon sequencing. (a) Emission spectra of narrow-band light-emitting diodes (LEDs) used in this study, with peak emissions at 742, 768 and 777 nm indicated by a–c, respectively. (b) Gross photosynthesis measured via an O₂ microsensor placed in a clump of agarose-embedded Chl f-containing cells. Different NIR irradiance was administered by the LEDs in a and by altering the distance of the LEDs to the embedded cells. (c) Phylogenetic affiliation of known Chl f and/or Chl d-containing cyanobacteria (highlighted in gray) and their respective habitat/place of isolation. Taxonomy was determined by clustering all known oxygenic phototrophs found in enrichment cultures from this study (at order level) into a single OTU (=292 bp length, see Supplementary Materials for details). Phylogeny was inferred using Maximum-likelihood in conjunction with the GTR +I +G nucleotide substitution model, tree stability was tested using bootstrapping with 100 replicates. The analysis involved 39 nucleotide sequences each truncated to a length of 292 bp. Here, the green-sulphur bacterium Chlorobium tepidum TLS was chosen as the outgroup.This advocates that cells from our enrichment culture are related to KC1 cells and supports, in conjunction with further morphological-, physiological- and ultrastructural evidence, that Chl f is extending the usable light spectrum for oxygenic photosynthesis in a cavernous low-light environment. Given the lifestyle and known habitats of recognized Chl d/f-producing cyanobacteria (Figure 2c), we propose that many, if not all, surface-associated cyanobacteria are intrinsically capable of producing far-red light-absorbing pigments and to actively employ them in oxygenic photosynthesis as a result of FaRLiP or similar, yet unknown, mechanisms.     

Genetics of Sexual Development: An Evolutionary Playground for Fish

Teleost fishes are the most species-rich clade of vertebrates and feature an overwhelming diversity of sex-determining mechanisms, classically grouped into environmental and genetic systems. Here, we review the recent findings in the field of sex determination in fish. In the past few years, several new master regulators of sex determination and other factors involved in sexual development have been discovered in teleosts. These data point toward a greater genetic plasticity in generating the male and female sex than previously appreciated and implicate novel gene pathways in the initial regulation of the sexual fate. Overall, it seems that sex determination in fish does not resort to a single genetic cascade but is rather regulated along a continuum of environmental and heritable factors.IN contrast to mammals and birds, cold-blooded vertebrates, and among them teleost fishes in particular, show a variety of strategies for sexual reproduction (Figure 1), ranging from unisexuality (all-female species) to hermaphroditism (sequential, serial, and simultaneous, including outcrossing and selfing species) to gonochorism (two separate sexes at all life stages). The underlying phenotypes are regulated by a variety of sex determination (SD) mechanisms that have classically been divided into two main categories: genetic sex determination (GSD) and environmental sex determination (ESD) (Figure 2).Open in a separate windowFigure 1Reproductive strategies in fish. Fish can be grouped according to their reproductive strategy into unisexuals, hermaphrodites, and gonochorists. Further subdivisions of these three categories are shown with pictures of species exemplifying the strategies. Fish images: Amphiprion clarkii courtesy of Sara Mae Stieb; Hypoplectrus nigricans courtesy of Oscar Puebla; Scarus ferrugineus courtesy of Moritz Muschick; Astatotilapia burtoni courtesy of Anya Theis; Poecilia formosa and Kryptolebias marmoratus courtesy of Manfred Schartl; Trimma sp. courtesy of Rick Winterbottom [serial hermaphroditism has been described in several species of the genus Trimma (Kuwamura and Nakashima 1998; Sakurai et al. 2009; and references therein)].Open in a separate windowFigure 2Sex-determining mechanisms in fish. Sex-determining systems in fish have been broadly classified into environmental and genetic sex determination. For both classes, the currently described subsystems are shown.Environmental factors impacting sex determination in fish are water pH, oxygen concentration, growth rate, density, social state, and, most commonly, temperature (for a detailed review on ESD see, e.g., Baroiller et al. 2009b and Stelkens and Wedekind 2010). As indicated in Figure 2, GSD systems in fish compose a variety of different mechanisms and have been reviewed in detail elsewhere (e.g., Devlin and Nagahama 2002; Volff et al. 2007).The GSD systems that have received the most scientific attention so far are those involving sex chromosomes, which either may be distinguishable cytologically (heteromorphic) or appear identical (homomorphic). In both cases, one sex is heterogametic (possessing two different sex chromosomes and hence producing two types of gametes) and the other one homogametic (a genotype with two copies of the same sex chromosome, producing only one type of gamete). A male-heterogametic system is called an XX-XY system, and female-heterogametic systems are denoted as ZZ-ZW. Both types of heterogamety exist in teleosts and are even found side by side in closely related species [e.g., tilapias (Cnaani et al. 2008), ricefishes (Takehana et al. 2008), or sticklebacks (Ross et al. 2009)]; for more details on the phylogenetic distribution of GSD mechanisms in teleost fish, see Mank et al. (2006). Note that sex chromosomes in fish are mostly homomorphic and not differentiated (Ohno 1974), which is in contrast to the degenerated Y and W chromosomes in mammals (Graves 2006) and birds (Takagi and Sasaki 1974), respectively. This is one possible explanation for the viable combination of different sex chromosomal systems within a single species or population of fish (Parnell and Streelman 2013) and could be a mechanistic reason why sex chromosome turnovers occur easily and frequently in this group (Mank and Avise 2009). Additionally, fish can have more complex sex chromosomal systems involving more than one chromosome pair (see Figure 2). Even within a single fish species, more than two sex chromosomes may occur at the same time, or more than two types of sex chromosomes may co-exist in the same species (Schultheis et al. 2006; Cioffi et al. 2013), which can sometimes be due to chromosome fusions (Kitano and Peichel 2012).Detailed insights on the gene level for GSD/sex chromosomal systems are currently available for only a limited number of fish species, and all but one of these cases involve a rather simple genetic system with male heterogamety and one major sex determiner (see below). The only exception is the widely used model species zebrafish (Danio rerio), which has a polyfactorial SD system implicating four different chromosomes (chromosomes 3, 4, 5, and 16) (Bradley et al. 2011; Anderson et al. 2012) and also environmental cues (Shang et al. 2006).In this review, we focus on newly described genetic sex-determining systems and possible mechanisms allowing their emergence in fishes, which are the most successful group of vertebrates with ∼30,000 species.     

Hydrocarbons Are Essential for Optimal Cell Size,Division, and Growth of Cyanobacteria

Cyanobacteria are intricately organized, incorporating an array of internal thylakoid membranes, the site of photosynthesis, into cells no larger than other bacteria. They also synthesize C15-C19 alkanes and alkenes, which results in substantial production of hydrocarbons in the environment. All sequenced cyanobacteria encode hydrocarbon biosynthesis pathways, suggesting an important, undefined physiological role for these compounds. Here, we demonstrate that hydrocarbon-deficient mutants of Synechococcus sp. PCC 7002 and Synechocystis sp. PCC 6803 exhibit significant phenotypic differences from wild type, including enlarged cell size, reduced growth, and increased division defects. Photosynthetic rates were similar between strains, although a minor reduction in energy transfer between the soluble light harvesting phycobilisome complex and membrane-bound photosystems was observed. Hydrocarbons were shown to accumulate in thylakoid and cytoplasmic membranes. Modeling of membranes suggests these compounds aggregate in the center of the lipid bilayer, potentially promoting membrane flexibility and facilitating curvature. In vivo measurements confirmed that Synechococcus sp. PCC 7002 mutants lacking hydrocarbons exhibit reduced thylakoid membrane curvature compared to wild type. We propose that hydrocarbons may have a role in inducing the flexibility in membranes required for optimal cell division, size, and growth, and efficient association of soluble and membrane bound proteins. The recent identification of C15-C17 alkanes and alkenes in microalgal species suggests hydrocarbons may serve a similar function in a broad range of photosynthetic organisms.Cyanobacteria (oxygenic photosynthetic bacteria) are found in nearly every environment on Earth and are major contributors to global carbon and nitrogen fixation (Galloway et al., 2004; Zwirglmaier et al., 2008). They are distinguished among prokaryotes in containing multiple internal thylakoid membranes, the site of photosynthesis, and a large protein compartment, the carboxysome, involved in carbon fixation. Despite these extra features, cyanobacteria can be as small as 0.6 µm in diameter (Raven, 1998).All cyanobacteria with sequenced genomes encode the pathway for the biosynthesis of hydrocarbons, implying an important, although as-yet-undefined, role for these compounds (Lea-Smith et al., 2015). The major forms are C15-C19 alkanes and alkenes, which can be synthesized from fatty acyl-acyl-carrier proteins (ACPs) by one or other of two separate pathways (Fig. 1; Schirmer et al., 2010; Mendez-Perez et al., 2011). The majority of species produce alkanes and alkenes via acyl-ACP reductase (FAR) and aldehyde deformylating oxygenase (FAD; Schirmer et al., 2010; Li et al., 2012; Coates et al., 2014; Lea-Smith et al., 2015). Cyanobacterial species lacking the FAR/FAD pathway synthesize alkenes via olefin synthase (Ols; Mendez-Perez et al., 2011; Coates et al., 2014; Lea-Smith et al., 2015). This suggests that hydrocarbons produced by either pathway serve a similar role in the cell. Homologs of FAR/FAD or Ols are not present in other bacteria or plant and algal species. However, C15-C17 alkanes and alkenes, synthesized by an alternate, uncharacterized pathway, were recently detected in a range of green microalgae, including Chlamydomonas reinhardtii, Chlorella variabilis NC64A, and several Nannochloropsis species (Sorigué et al., 2016). In C. reinhardtii, hydrocarbons were primarily localized to the chloroplast, which originated in evolution from a cyanobacterium that was engulfed by a host organism (Howe et al., 2008). Hydrocarbons may therefore have a similar role in cyanobacteria, some green microalgae species, and possibly a broader range of photosynthetic organisms.Open in a separate windowFigure 1.Hydrocarbon biosynthesis is encoded in all sequenced cyanobacteria. Detailed are the two hydrocarbon biosynthetic pathways, indicated in blue and red, respectively, in cyanobacteria. The number of species encoding the enzymes in each pathway is indicated.Hydrocarbons act as antidesiccants, waterproofing agents, and signaling molecules in insects (Howard and Blomquist, 2005) and prevent water loss, ensure pollen viability, and influence pathogen interactions in plants (Kosma et al., 2009; Bourdenx et al., 2011). However, the function of hydrocarbons in cyanobacteria has not been determined. Characterization of cyanobacterial hydrocarbon biosynthesis pathways has provided the basis for investigating synthetic microbial biofuel systems, which may be a renewable substitute for fossil fuels (Schirmer et al., 2010; Choi and Lee, 2013; Howard et al., 2013). However, secretion of long-chain hydrocarbons from the cell into the medium, which is likely essential for commercially viable production, has not been observed in the absence of a membrane solubilization agent (Schirmer et al., 2010; Tan et al., 2011). Cyanobacterial hydrocarbons also have a significant environmental role. Due to the abundance of cyanobacteria in the environment, hydrocarbon production is considerable, with hundreds of millions of tons released into the ocean per annum following cell death (Lea-Smith et al., 2015). This production may be sufficient to sustain populations of hydrocarbon-degrading bacteria, which can then play an important role in consuming anthropogenic oil spills (Lea-Smith et al., 2015).Here, we investigated the cellular location and role of hydrocarbons in both spherical Synechocystis sp. PCC 6803 (Synechocystis) and rod-shaped Synechococcus sp. PCC 7002 (Synechococcus) cells. We developed a model of the cyanobacterial membrane, which indicated that hydrocarbons aggregate in the middle of the lipid bilayer and, when present at levels observed in cells, lead to membrane swelling associated with pools of hydrocarbon. This suggested that alkanes may facilitate membrane curvature. In vivo measurements of Synechococcus thylakoid membrane conformation are consistent with this model.     

The evolution of genomic imprinting: theories,predictions and empirical tests

The epigenetic phenomenon of genomic imprinting has motivated the development of numerous theories for its evolutionary origins and genomic distribution. In this review, we examine the three theories that have best withstood theoretical and empirical scrutiny. These are: Haig and colleagues'' kinship theory; Day and Bonduriansky''s sexual antagonism theory; and Wolf and Hager''s maternal–offspring coadaptation theory. These theories have fundamentally different perspectives on the adaptive significance of imprinting. The kinship theory views imprinting as a mechanism to change gene dosage, with imprinting evolving because of the differential effect that gene dosage has on the fitness of matrilineal and patrilineal relatives. The sexual antagonism and maternal–offspring coadaptation theories view genomic imprinting as a mechanism to modify the resemblance of an individual to its two parents, with imprinting evolving to increase the probability of expressing the fitter of the two alleles at a locus. In an effort to stimulate further empirical work on the topic, we carefully detail the logic and assumptions of all three theories, clarify the specific predictions of each and suggest tests to discriminate between these alternative theories for why particular genes are imprinted.The discovery of genomic imprinting, where the expression of an allele depends on its parental origin, motivated a diversity of theories attempting to explain its existence (Spencer and Clark, 2014). Three main theories have withstood scrutiny and are the focus of this review: Haig and colleagues'' kinship theory (Haig and Westoby, 1989; Haig, 2000a, 2004); Day and Bonduriansky''s (2004) sexual antagonism theory (see also Bonduriansky, 2007); and Wolf and Hager''s (2006) maternal–offspring coadaptation theory (see also Wolf and Hager, 2009; Wolf, 2013). Although these theories rest on different logic and fundamental assumptions, they share a critical common feature: some process creates a selective asymmetry between the maternally and paternally inherited allelic copies at a locus that causes selection to favor differential expression of the alleles (typically silencing of one of the copies) (Figures 1, ​,2,2, ​,33).Open in a separate windowFigure 1The kinship theory of genomic imprinting has two prerequisites: first, epigenetic marks that differentiate matrigenes from patrigenes; second, a difference in the relatedness of matrigenes and patrigenes to the social group. (a) The social group in the example depicted is a single litter of offspring, and multiple mating produces a relatedness asymmetry between half-siblings. The relatedness for matrigenes is ½ and the relatedness for patrigenes is 0. (Other sources of relatedness asymmetry are possible—e.g., sex-biased dispersal or high fitness variance in one sex—and social interactions are not limited to the juvenile period only). (b) The kinship theory envisions kin selection acting independently on genes of maternal and paternal origin and solves for the evolutionarily stable gene expression strategy for matrigenes and patrigenes. (c) For genes where the matrigenic allele''s optimum expression level is higher than that of the patrigene''s (e.g., a fetal growth inhibitor), the kinship theory predicts silencing of the patrigenic allele; for genes with the opposite effect (e.g., a fetal growth enhancer), the prediction is for patrigenic expression.Open in a separate windowFigure 2(a, b) The sexual antagonism theory of genomic imprinting starts with sexually antagonistic selection, which produces different allele frequencies, shown as pie charts, for genes of maternal and paternal origin. (c, d) Natural selection favors individuals that are able to express the fitter of the two alleles at a locus, which for males will be the patrigenic allele and for females will be the matrigenic allele. (In addition, the sexual antagonism theory may predict matrigenic or patrigenic expression in both sexes, such that the expressed allele derives from the parental sex that experiences stronger selection pressure. This scenario is not depicted).Open in a separate windowFigure 3(a) The maternal–offspring coadaptation theory of genomic imprinting relies on the correlation of genes in the mother and genes of maternal origin in the offspring (shown in light blue). (b) Fitness of offspring is determined by the interaction (shown in dark purple) between the phenotypes of mothers and offspring. (c) Imprinted silencing of the patrigenic allele can be favored for either of two reasons, depending on the genetic architecture of the interacting phenotypes. First, when a single gene governs the interaction and phenotypic matching between mothers and their offspring produces high fitness, then silencing of the patrigenic allele is beneficial to offspring because it raises the probability of producing a match. Second, if different loci are involved in the phenotypic interaction, past correlational selection will have produced a covariance between them, generating haplotypes with combinations of alleles that interact well together. (N.B. This multi-locus interaction is not depicted in the figure.) The offspring is more likely to inherit from its mother an allele that interacts well with the alleles in the mother''s genotype. This also favors the imprinted silencing of the patrigenic allele because it raises the probability that the offspring expresses an allele that makes for a good interaction with the maternal phenotype.Here we provide an overview of the fundamental logic and critical assumptions of these models. We then derive predictions that can be used to distinguish between theories. In doing so, we also highlight ambiguities in and overlap between the predictions they make, with a goal of motivating further research. In addition, we suggest some areas for future work that will test some of these predictions.     

Ratiometric Imaging of the T-Cell Actin Cytoskeleton Reveals the Nature of Receptor-Induced Cytoskeletal Enrichment

The T-cell actin cytoskeleton mediates adaptive immune system responses to peptide antigens by physically directing the motion and clustering of T-cell receptors (TCRs) on the cell surface. When TCR movement is impeded by externally applied physical barriers, the actin network exhibits transient enrichment near the trapped receptors. The coordinated nature of the actin density fluctuations suggests that they are composed of filamentous actin, but it has not been possible to eliminate de novo polymerization at TCR-associated actin polymerizing factors as an alternative cause. Here, we use a dual-probe cytoskeleton labeling strategy to distinguish between stable and polymerizing pools of actin. Our results suggest that TCR-associated actin consists of a relatively high proportion of the stable cytoskeletal fraction and extends away from the cell membrane into the cell. This implies that actin enrichment at mechanically trapped TCRs results from three-dimensional bunching of the existing filamentous actin network.The T-cell actin cytoskeleton is critical for proper antigen recognition by the mammalian adaptive immune system. During T-cell receptor (TCR) triggering by antigen peptides presented on major histocompatibility proteins (pMHCs) on the surfaces of antigen-presenting cells (APCs), the T-cell actin cytoskeleton adopts a pattern of centrosymmetric retrograde flow (1–3). This simultaneously promotes further TCR triggering (4) and rearranges various T-cell membrane proteins and their APC counterparts into an organized cell-cell interface termed the immunological synapse (IS) (5–7). During this process, TCRs form microclusters that move to the center of the IS in an actin-dependent manner (8,9). When engineered physical barriers interrupt the centripetal motion of TCR clusters, actin flow slows near the pinned microclusters, and the cytoskeletal network transiently accumulates and dissipates at the sites (10,11). The amplitude and duration of the induced cytoskeletal fluctuations are much greater than would be expected for a random distribution of independent objects, indicating that the actin in the local environment is coordinated. Whether this coordination arises from a rearrangement in the existing F-actin network or represents de novo polymerization of the cytoskeleton, as predicted by the association of TCRs with actin polymerizing factors (12), remains unclear. Here, we use a dual-probe cytoskeleton labeling approach that has previously been applied to distinguish between stable and dynamic populations of actin by exploiting the different relative affinities of monomeric actin and actin-binding proteins toward each population (13). This strategy reveals that TCR-associated actin is composed primarily of the stable cytoskeletal fraction and that local enrichment results from three-dimensional bunching of the existing filamentous actin network.Primary T cells from mice transgenic for the AND TCR were triggered using synthetic APCs consisting of supported lipid bilayers functionalized with pMHC and the integrin ligand intercellular adhesion molecule 1. Nanopatterned metal grids on the bilayer substrate acted as diffusion barriers that prevented lateral transport of TCR-pMHC complexes (14,15). Transient enrichment of actin at TCR clusters trapped at these barriers was visualized using fluorescent fusions of actin itself (mKate2-β-actin) and the F-actin binding domain of utrophin (EGFP-UtrCH). Such a dual-probe strategy theoretically allows for discrimination between different pools of actin: dynamic populations characterized by high polymerization and/or short filament fragments tend to be relatively better labeled by direct actin fusions whereas stable populations composed of longer filaments can support higher labeling by fluorescent fusions of F-actin binding proteins. This visualization method has been validated in Xenopus oocytes, where it distinguishes actin populations during wound healing (13). It has not been explicitly applied to T cells; however, simultaneous labeling of the Jurkat cell cytoskeleton using EGFP-actin and Alexa 568-phalloidin reveals distinct populations of actin consistent with the results expected from Xenopus (13,16).Our results show that the T-cell periphery is relatively enriched in mKate2-β-actin (Fig. 1 C, box 1), while EGFP-UtrCH dominates toward the center of the IS (Fig. 1 C, box 2). We infer from this probe distribution that the cytoskeleton at the T-cell periphery is composed of short fragments and is a site of active polymerization, whereas at the center of the IS, actin filaments are longer and predominantly stable. This is consistent with previous models of the T-cell actin network (3,16). An effective way to highlight each of these cytoskeletal regions is to consider the relative ratios of the two probes at each location. In this case, a high UtrCH/actin ratio corresponds to stable actin, and a high actin/UtrCH ratio corresponds to dynamic actin (Fig. 1 D). When T cells are treated with cytochalasin D, an inhibitor of actin polymerization, the overall UtrCH/actin ratio of the cell decreases as would be expected from a general decrease in polymerized actin (see Movie S7 and Movie S8 in the Supporting Material). However, it should be noted that photobleaching can also shift the UtrCH/actin ratio over time. We limit quantitative analysis of the ratio to its spatial gradients at a single time point, but such analysis is possible in systems that permit rigorous calibration for probe expression and photobleaching.Open in a separate windowFigure 1Ratiometric imaging of the cytoskeleton in live T cells distinguishes between dynamic and stable actin populations. (A) mKate2-β-actin, (B) EGFP-UtrCH, and (C) merged images of a triggered T cell show different actin pools. The cutouts in panel C correspond to (1) a region high in dynamic actin featuring short, polymerizing filaments and/or actin monomers and (2) a region with a stable actin population featuring longer filaments to which UtrCH can bind. (D) The UtrCH/actin ratio image highlights pools of relatively high UtrCH (red) or actin (blue). (Scale bars: 5 μm.)Actin enrichment at trapped TCR clusters incorporates both mKate2-β-actin (Fig. 2, A and C) and EGFP-UtrCH (Fig. 2, B and C). The relative UtrCH/actin ratio at these sites (Fig. 2 D, box 2) is quite high relative to nearby background areas (Fig. 2 D, box 1), indicating that the actin is derived primarily from the stable actin population.Open in a separate windowFigure 2Receptor-induced cytoskeletal enrichment at sites of pinned TCRs corresponds to a primarily stable actin fraction. (A) mKate2-β-actin, (B) EGFP-UtrCH, and (C) merged images of a triggered T cell interacting with a nanopatterned supported lipid bilayer show actin enrichment corresponding to putative sites of pinned TCRs. (D) The UtrCH/actin ratio is high at sites displaying actin enrichment, indicating a primarily stable actin fraction in (1) these regions compared to (2) nearby background areas. (Scale bars: 5 μm.)The three-dimensional distribution of TCR-associated actin was analyzed in dual-labeled live T cells using a spinning disk confocal microscope. The recordings show actin extending away from the cell membrane in the vicinity of trapped TCRs, while the rest of the actin cytoskeleton remains relatively flat (Fig. 3 and see Fig. S1 in the Supporting Material). These protrusions of actin away from the membrane surface are predominantly composed of stable, filamentous actin, as indicated by their relatively high UtrCH/actin ratio (Fig. 3 B).Open in a separate windowFigure 3Three-dimensional ratiometric imaging shows that actin enrichment extends away from the cell membrane. Single planes from (A) merged mKate2-β-actin and EGFP-UtrCH and (B) UtrCH/actin ratio three-dimensional stacks show actin enrichment at the cell membrane. Cutouts represent Z projections passing through sites of (1) enrichment and (2) nearby background regions. The color distribution in panel B is analogous to that in Figs. 1D and ​and22D, and is omitted for clarity. (Scale bar: 5 μm in the x axis only. Scale box: 1 μm.)Our interpretation of these results is that the filamentous actin network is relatively dense at sites of pinned TCRs. This is the simplest explanation out of several possibilities, one of which is formin-mediated mKate2-β-actin-deficient actin nucleation (17). Filament bunching at pinned TCRs can arise from consistent biophysical properties without assuming heterogeneity between the biochemistry of these receptors and other actin-associated proteins such as those at the cell edge, where locally high probe ratios are absent.Although TCRs are intentionally trapped as part of this experimental strategy, it is likely APCs can naturally impede TCR ligand mobilities under certain circumstances, and this has been shown to impact T-cell signaling (18,19). Actin architecture near cell surface proteins has been extensively studied in focal adhesions of fibroblasts (20), but the lack of stress fibers in T cells makes it unlikely that the two structures are similar. Thus, receptor-induced cytoskeletal enrichment at TCR clusters adds to the catalog of actin behaviors in situ, which is conveniently probed by techniques such as ratiometric dual-probe imaging in live cells. These techniques can be coupled to various spatial analysis algorithms to further extend their utility.     

Conformational States of Melittin at a Bilayer Interface

The distribution of peptide conformations in the membrane interface is central to partitioning energetics. Molecular-dynamics simulations enable characterization of in-membrane structural dynamics. Here, we describe melittin partitioning into dioleoylphosphatidylcholine lipids using CHARMM and OPLS force fields. Although the OPLS simulation failed to reproduce experimental results, the CHARMM simulation reported was consistent with experiments. The CHARMM simulation showed melittin to be represented by a narrow distribution of folding states in the membrane interface.Unstructured peptides fold into the membrane interface because partitioned hydrogen-bonded peptide bonds are energetically favorable compared to free peptide bonds (1–3). This folding process is central to the mechanisms of antimicrobial and cell-penetrating peptides, as well as to lipid interactions and stabilities of larger membrane proteins (4). The energetics of peptide partitioning into membrane interfaces can be described by a thermodynamic cycle (Fig. 1). State A is a theoretical state representing the fully unfolded peptide in water, B is the unfolded peptide in the membrane interface, C is the peptide in water, and D is the folded peptide in the membrane. The population of peptides in solution (State C) is best described as an ensemble of folded and unfolded conformations, whereas the population of peptides in State D generally is assumed to have a single, well-defined helicity, as shown in Fig. 1 A (5). Given that, in principle, folding in solution and in the membrane interface should follow the same basic rules, peptides in state D could reasonably be assumed to also be an ensemble. A fundamental question (5) is therefore whether peptides in state D can be correctly described as having a single helicity. Because differentiating an ensemble of conformations and a single conformation may be an impossible experimental task (5), molecular-dynamics (MD) simulations provide a unique high-resolution view of the phenomenon.Open in a separate windowFigure 1Thermodynamic cycles for peptide partitioning into a membrane interface. States A and B correspond to the fully unfolded peptide in solution and membrane interface, respectively. The folded peptide in solution is best described as an ensemble of unfolded and folded conformations (State C). State D is generally assumed to be one of peptides with a narrow range of conformations, but the state could actually be an ensemble of states as in the case of State C.Melittin is a 26-residue, amphipathic peptide that partitions strongly into membrane interfaces and therefore has become a model system for describing folding energetics (3,6–8). Here, we describe the structural dynamics of melittin in a dioleoylphosphatidylcholine (DOPC) bilayer by means of two extensive MD simulations using two different force fields.We extended a 12-ns equilibrated melittin-DOPC system (9) by 17 μs using the Anton specialized hardware (10) with the CHARMM22/36 protein/lipid force field and CMAP correction (11,12) (see Fig. S1 and Fig. S2 in the Supporting Material). To explore force-field effects, a similar system was simulated for 2 μs using the OPLS force field (13) (see Methods in the Supporting Material). In agreement with x-ray diffraction measurements on melittin in DOPC multilayers (14), melittin partitioned spontaneously into the lipid headgroups at a position below the phosphate groups at similar depth as glycerol/carbonyl groups (Fig. 2).Open in a separate windowFigure 2Melittin partitioned into the polar headgroup region of the lipid bilayer. (A) Snapshot of the simulation cell showing two melittin molecules (MLT1 and MLT2, in yellow) at the lipid-water interface. (B) Density cross-section of the simulation cell extracted from the 17-μs simulation. The peptides are typically located below the lipid phosphate (PO4) groups, in a similar depth as the glycerol/carbonyl (G/C) groups.To describe the secondary structure for each residue, we defined helicity by backbone dihedral angles (φ, ψ) within 30° from the ideal α-helical values (–57°, –47°). The per-residue helicity in the CHARMM simulation displays excellent agreement with amide exchange rates from NMR measurements that show a proline residue to separate two helical segments, which are unfolded below Ala⁵ and above Arg²² (15) (Fig. 3 A). In contrast, the OPLS simulation failed to reproduce the per-residue helicity except for a short central segment (see Fig. S3).Open in a separate windowFigure 3Helicity and conformational distribution of melittin as determined via MD simulation. (A) Helicity per residue for MLT1 and MLT2. (B) Corresponding evolution of the helicity. (C) Conformational distributions over the entire 17-μs simulation.Circular dichroism experiments typically report an average helicity of ∼70% for melittin at membrane interfaces (3,6,16,17), but other methods yield average helicities as high as 85% (15,18). Our CHARMM simulations are generally consistent with the experimental results, especially amide-exchange measurements (15); melittin helicity averaged to 78% for MLT1, whereas MLT2 transitioned from 75% to 89% helicity at t ≈ 8 μs, with an overall average helicity of 82% (Fig. 3 B). However, in the OPLS simulation, melittin steadily unfolds over the first 1.3 μs, after which the peptide remains only partly folded, with an average helicity of 33% (see Fig. S3). Similar force-field-related differences in peptide helicity were recently reported, albeit at shorter timescales (19). Although suitable NMR data are not presently available, we have computed NMR quadrupolar splittings for future reference (see Fig. S4).To answer the question asked in this article—whether the conformational space of folded melittin in the membrane interface can be described by a narrow distribution—the helicity distributions for the equilibrated trajectories are shown in Fig. 3 C. Whereas MLT1 in the CHARMM simulation produces a single, narrow distribution of the helicity, MLT2 has a bimodal distribution as a consequence of the folding event at t ≈ 8 μs (Fig. 3 C). We note that CHARMM force fields have a propensity for helix-formation and this transition might therefore be an artifact. We performed a cluster analysis to describe the structure of the peptide in the membrane interface. The four most populated conformations in the CHARMM simulation are shown in Fig. 4. The dominant conformation for both peptides was a helix kinked at G12 and unfolded at the last 5–6 residues of the C-terminus. The folding transition of MLT2 into a complete helix is visible by the 48% occupancy of a fully folded helix.Open in a separate windowFigure 4Conformational clusters of the two melittin peptides (MLT1 and MLT2) from the 17-μs CHARMM simulation in DOPC. Clustering is based on Cα-RMSD with a cutoff criterion of 2 Å.We conclude that the general assumption when calculating folding energetics holds: Folded melittin partitioned into membrane interfaces can be described by a narrow distribution of conformations. Furthermore, extended (several microsecond) simulations are needed to differentiate force-field effects. Although the CHARMM and OPLS simulations would seem to agree for the first few hundred nanoseconds, the structural conclusions differ drastically with longer trajectories, with CHARMM parameters being more consistent with experiments. However, as implied by the difference in substate distributions between MLT1 and MLT2, 17 μs might not be sufficient to observe the fully equilibrated partitioning process. The abrupt change in MLT2 might indicate that the helicity will increase to greater than experimentally observed in a sufficiently long simulation. On the other hand, it could be nothing more than a transient fluctuation. Increased sampling will provide further indicators of convergence of the helix partitioning process.     

Novel Growth Regime of MDCK II Model Tissues on Soft Substrates

It is well established that MDCK II cells grow in circular colonies that densify until contact inhibition takes place. Here, we show that this behavior is only typical for colonies developing on hard substrates and report a new growth phase of MDCK II cells on soft gels. At the onset, the new phase is characterized by small, three-dimensional droplets of cells attached to the substrate. When the contact area between the agglomerate and the substrate becomes sufficiently large, a very dense monolayer nucleates in the center of the colony. This monolayer, surrounded by a belt of three-dimensionally packed cells, has a well-defined structure, independent of time and cluster size, as well as a density that is twice the steady-state density found on hard substrates. To release stress in such dense packing, extrusions of viable cells take place several days after seeding. The extruded cells create second-generation clusters, as evidenced by an archipelago of aggregates found in a vicinity of mother colonies, which points to a mechanically regulated migratory behavior.Studying the growth of cell colonies is an important step in the understanding of processes involving coordinated cell behavior such as tissue development, wound healing, and cancer progression. Apart from extremely challenging in vivo studies, artificial tissue models are proven to be very useful in determining the main physical factors that affect the cooperativity of cells, simply because the conditions of growth can be very well controlled. One of the most established cell types in this field of research is the Madin-Darby canine kidney epithelial cell (MDCK), originating from the kidney distal tube (1). A great advantage of this polarized epithelial cell line is that it retained the ability for contact inhibition (2), which makes it a perfect model system for studies of epithelial morphogenesis.Organization of MDCK cells in colonies have been studied in a number of circumstances. For example, it was shown that in three-dimensional soft Matrigel, MDCK cells form a spherical enclosure of a lumen that is enfolded by one layer of polarized cells with an apical membrane exposed to the lumen side (3). These structures can be altered by introducing the hepatocyte growth factor, which induces the formation of linear tubes (4). However, the best-studied regime of growth is performed on two-dimensional surfaces where MDCK II cells form sheets and exhibit contact inhibition. Consequently, the obtained monolayers are well characterized in context of development (5), mechanical properties (6), and obstructed cell migration (7–9).Surprisingly, in the context of mechanics, several studies of monolayer formation showed that different rigidities of polydimethylsiloxane gels (5) and polyacrylamide (PA) gels (9) do not influence the nature of monolayer formation nor the attainable steady-state density. This is supposedly due to long-range forces between cells transmitted by the underlying elastic substrate (9). These results were found to agree well with earlier works on bovine aortic endothelial cells (10) and vascular smooth muscle cells (11), both reporting a lack of sensitivity of monolayers to substrate elasticity. Yet, these results are in stark contrast with single-cell experiments (12–15) that show a clear response of cell morphology, focal adhesions, and cytoskeleton organization to substrate elasticity. Furthermore, sensitivity to the presence of growth factors that are dependent on the elasticity of the substrate in two (16) and three dimensions (4) makes this result even more astonishing. Therefore, we readdress the issue of sensitivity of tissues to the elasticity of the underlying substrate and show that sufficiently soft gels induce a clearly different tissue organization.We plated MDCK II cells on soft PA gels (Young’s modulus E = 0.6 ± 0.2 kPa), harder PA gels (E = 5, 11, 20, 34 kPa), and glass, all coated with Collagen-I. Gels were prepared following the procedure described in Rehfeldt et al. (17); rigidity and homogeneity of the gels was confirmed by bulk and microrheology (see the Supporting Material for comparison). Seeding of MDCK II cells involved a highly concentrated solution dropped in the middle of a hydrated gel or glass sample. For single-cell experiments, cells were dispersed over the entire dish. Samples were periodically fixed up to Day 12, stained for nuclei and actin, and imaged with an epifluorescence microscope. Details are described in the Supporting Material.On hard substrates and glass it was found previously that the area of small clusters expands exponentially until the movement of the edge cannot keep up with the proliferation in the bulk (5). Consequently, the bulk density increases toward the steady state, whereas the density of the edge remains low. At the same time, the colony size grows subexponentially (5). This is what we denote “the classical regime of growth”. Our experiments support these observations for substrates with E ≥ 5 kPa. Specifically, on glass, colonies start as small clusters of very low density of 700 ± 200 cells/mm² (Fig. 1, A and B), typically surrounded by a strong actin cable (Fig. 1, B and C). Interestingly, the spreading area of single cells (Fig. 1 A) on glass was found to be significantly larger, i.e., (2.0 ± 0.9) × 10⁻³ mm². After Day 4 (corresponding cluster area of 600 ± 100 mm²), the density in the center of the colony reached the steady state with 6,800 ± 500 cells/mm², whereas the mean density of the edge profile grew to 4,000 ± 500 cells/mm². This density was retained until Day 12 (cluster area 1800 ± 100 mm²), which is in agreement with previous work (9).Open in a separate windowFigure 1Early phase of cluster growth on hard substrates. (A) Well-spread single cells, and small clusters with a visible actin cable 6 h after seeding. (B) Within one day, clusters densify and merge, making small colonies. (C) Edge of clusters from panel B.In colonies grown on 0.6 kPa gels, however, we encounter a very different growth scenario. The average spreading area of single cells is (0.34 ± 0.3) × 10⁻³ mm², which is six times smaller than on glass substrates (Fig. 2 A). Clusters of only few cells show that cells have a preference for cell-cell contacts (a well-established flat contact zone can be seen at the cell-cell interface in Fig. 2 A) rather than for cell-substrate contacts (contact zone is diffusive and the shape of the cells appears curved). The same conclusion emerges from the fact that dropletlike agglomerates, resting on the substrate, form spontaneously (Fig. 2 A), and that attempts to seed one single cluster of 90,000 cells fail, resulting in a number of three-dimensional colonies (Fig. 2 A). When the contact area with the substrate exceeds 4.7 × 10⁻³ mm², a monolayer appears in the center of such colonies (Fig. 2 B). The colonies can merge, and if individual colonies are small, the collapse into a single domain is associated with the formation of transient irregular structures (Fig. 2 B). Ultimately, large elliptical colonies (average major/minor axis of e = 1.8 ± 0.6) with a smooth edge are formed (Fig. 2 C), unlike on hard substrates where circular clusters (e = 1.06 ± 0.06) with a ragged edge comprise the characteristic phenotype.Open in a separate windowFigure 2Early phase of cluster growth on soft substrates. (A) Twelve hours after seeding, single cells remain mostly round and small. They are found as individual, or within small, three-dimensional structures (top). The latter nucleate a monolayer in their center (bottom), if the contact area with the substrate exceeds ∼5 × 10⁻³ mm². (B) Irregularly-shaped clusters appear due to merging of smaller droplets. A stable monolayer surrounded by a three-dimensional belt of densely packed cells is clearly visible, even in larger structures. (C) All colonies are recorded on Day 4.Irrespective of cluster size, in the new regime of growth, the internal structure is built of two compartments (Fig. 2 B):

• 1.The first is the edge (0.019 ± 0.05-mm wide), a three-dimensional structure of densely packed cells. This belt is a signature of the new regime because on hard substrates the edge is strictly two-dimensional (Fig. 1 C).
• 2.The other is the centrally placed monolayer with a spatially constant density that is very weakly dependent on cluster size and age (Fig. 3). The mean monolayer density is 13,000 ± 2,000 cells/mm², which is an average over 130 clusters that are up to 12 days old and have a size in the range of 10⁻³ to 10 mm², each shown by a data point in Fig. 3. This density is twice the steady-state density of the bulk tissue in the classical regime of growth.Open in a separate windowFigure 3Monolayer densities in colonies grown on 0.6 kPa substrates, as a function of the cluster size and age. Each cluster is represented by a single data point signifying its mean monolayer density. (Black lines) Bulk and (red dashed lines) edge of steady-state densities from monolayers grown on glass substrates. Error bars are omitted for clarity, but are discussed in the Supporting Material.

Until Day 4, the monolayer is very homogeneous, showing a nearly hexagonal arrangement of cells. From Day 4, however, defects start to appear in the form of small holes (typical size of (0.3 ± 0.1) × 10⁻³ mm²). These could be attributed to the extrusions of viable cells, from either the belt or areas of increased local density in the monolayer (inset in Fig. 4). This suggests that extrusions serve to release stress built in the tissue, and, as a consequence, the overall density is decreased.Open in a separate windowFigure 4Cell nuclei within the mother colony and in the neighboring archipelago of second-generation clusters grown on 0.6 kPa gels at Day 12. (Inset; scale bar = 10 μm) Scar in the tissue, a result of a cell-extrusion event. (Main image; scale bar = 100 μm) From the image of cell nuclei (left), it is clear that there are no cells within the scar, whereas the image of actin (right) shows that the cytoplasm of the cells at the edge has closed the hole.Previous reports suggest that isolated MDCK cells undergo anoikis 8 h after losing contact with their neighbors (18). However, in this case, it appears that instead of dying, the extruded cells create new colonies, which can be seen as an archipelago surrounding the mother cluster (Fig. 4). The viability of off-cast cells is further evidenced by the appearance of single cells and second-generation colonies with sizes varying over five orders of magnitude, from Day 4 until the end of the experiment, Day 12. Importantly, no morphological differences were found in the first- and second-generation colonies.In conclusion, we show what we believe to be a novel phase of growth of MDCK model tissue on soft PA gels (E = 0.6 kPa) that, to our knowledge, despite previous similar efforts (9), has not been observed before. This finding is especially interesting in the context of elasticity of real kidneys, for which a Young’s modulus has been found to be between 0.05 and 5 kPa (19,20). This coincides with the elasticity of substrates studied herein, and opens the possibility that the newly found phase of growth has a particular biological relevance. Likewise, the ability to extrude viable cells may point to a new migratory pathway regulated mechanically by the stresses in the tissue, the implication of which we hope to investigate in the future.     

3D-SIM Super-resolution of FtsZ and Its Membrane Tethers in Escherichia coli Cells

FtsZ, a bacterial homolog of eukaryotic tubulin, assembles into the Z ring required for cytokinesis. In Escherichia coli, FtsZ interacts directly with FtsA and ZipA, which tether the Z ring to the membrane. We used three-dimensional structured illumination microscopy to compare the localization patterns of FtsZ, FtsA, and ZipA at high resolution in Escherichia coli cells. We found that FtsZ localizes in patches within a ring structure, similar to the pattern observed in other species, and discovered that FtsA and ZipA mostly colocalize in similar patches. Finally, we observed similar punctate and short polymeric structures of FtsZ distributed throughout the cell after Z rings were disassembled, either as a consequence of normal cytokinesis or upon induction of an endogenous cell division inhibitor.The assembly of the bacterial tubulin FtsZ has been well studied in vitro, but the fine structure of the cytokinetic Z ring it forms in vivo is not well defined. Super-resolution microscopy methods including photoactivated localization microscopy (PALM) and three-dimensional-structured illumination microscopy (3D-SIM) have recently provided a more detailed view of Z-ring structures. Two-dimensional PALM showed that Z rings in Escherichia coli are likely composed of loosely-bundled dynamic protofilaments (1,2). Three-dimensional PALM studies of Caulobacter crescentus initially showed that Z rings were comprised of loosely bundled protofilaments forming a continuous but dynamic ring (1–3). However, a more recent high-throughput study showed that the Z rings of this bacterium are patchy or discontinuous (4), similar to Z rings of Bacillus subtilis and Staphylococcus aureus using 3D-SIM (5). Strauss et al. (5) also demonstrated that the patches in B. subtilis Z rings are highly dynamic.Assembly of the Z ring is modulated by several proteins that interact directly with FtsZ and enhance assembly or disassembly (6). For example, FtsA and ZipA promote ring assembly in E. coli by tethering it to the cytoplasmic membrane (7,8). SulA is an inhibitor of FtsZ assembly, induced only after DNA damage, which sequesters monomers of FtsZ to prevent its assembly into a Z ring (9). Our initial goals were to visualize Z rings in E. coli using 3D-SIM, and then examine whether any FtsZ polymeric structures remain after SulA induction. We also asked whether FtsA and ZipA localized in patchy patterns similar to those of FtsZ.We used a DeltaVision OMX V4 Blaze microscope (Applied Precision, GE Healthcare, Issaquah, WA) to view the high-resolution localization patterns of FtsZ in E. coli cells producing FtsZ-GFP (Fig. 1). Three-dimensional views were reconstructed using softWoRx software (Applied Precision). To rule out GFP artifacts, we also visualized native FtsZ from a wild-type strain (WM1074) by immunofluorescence (IF).Open in a separate windowFigure 1Localization of FtsZ in E. coli. (A) Cell with a Z ring labeled with FtsZ-GFP. (B) Rotated view of Z ring in panel A. (C) Cell with a Z ring labeled with DyLight 550 (Thermo Fisher Scientific, Waltham, MA). (D) Rotated view of Z ring in panel C. (B1 and D1) Three-dimensional surface intensity plots of Z rings in panels B and D, respectively. (E) A dividing cell producing FtsZ-GFP. The cell outline is shown in the schematic. (Asterisk) Focus of FtsZ localization; (open dashed ovals) filamentous structures of FtsZ. Three-dimensional surface intensity plots were created using the software ImageJ (19). Scale bars, 1 μm.Both FtsZ-GFP (Fig. 1, A, B, and B1) and IF staining for FtsZ (Fig. 1, C, D, and D1) consistently localized to patches around the ring circumference, similar to the B. subtilis and C. crescentus FtsZ patterns (4,5). Analysis of fluorescence intensities (see Fig. S1, A and B, in the Supporting Material) revealed that the majority of Z rings contain one or more gaps in which intensity decreases to background levels (82% for FtsZ-GFP and 69% for IF). Most rings had 3–5 areas of lower intensity, but only a small percentage of these areas had fluorescence below background intensity (34% for FtsZ-GFP and 21% for IF), indicating that the majority of areas with lower intensity contain at least some FtsZ.To elucidate how FtsZ transitions from a disassembled ring to a new ring, we imaged a few dividing daughter cells before they were able to form new Z rings (Fig. 1 E). Previous conventional microscopy had revealed dynamic FtsZ helical structures (10), but the resolution had been insufficient to see further details. Here, FtsZ visualized in dividing cells by 3D-SIM localized throughout as a mixture of patches and randomly-oriented short filaments (asterisk and dashed oval in Fig. 1, respectively). These structures may represent oligomeric precursors of Z ring assembly.To visualize FtsZ after Z-ring disassembly another way, we overproduced SulA, a protein that blocks FtsZ assembly. We examined E. coli cells producing FtsZ-GFP after induction of sulA expression from a pBAD33-sulA plasmid (pWM1736) with 0.2% arabinose. After 30 min of sulA induction, Z rings remained intact in most cells (Fig. 2 A and data not shown). The proportion of cellular FtsZ-GFP in the ring before and after induction of sulA was consistent with previous data (data not shown) (1,11).Open in a separate windowFigure 2Localization of FtsZ after overproduction of SulA. (A) Cell producing FtsZ-GFP after 0.2% arabinose induction of SulA for 30 min. (B) After 45 min. (B1) Magnified cell shown in panel B. (C) Cell producing native FtsZ labeled with AlexaFluor 488 (Life Technologies, Carlsbad, CA) 30 min after induction; (D) 45 min after induction. (D1) Magnified cell shown in panel D. Scale bars, 1 μm. (Asterisk) Focus of FtsZ localization; (open dashed ovals) filamentous structures of FtsZ.Notably, after 45 min of sulA induction, Z rings were gone (Fig. 2, B and B1), replaced by numerous patches and randomly-oriented short filaments (asterisk and dashed ovals in Fig. 2), similar to those observed in a dividing cell. FtsZ normally rapidly recycles from free monomers to ring-bound polymers (11), but a critical concentration of SulA reduces the pool of available FtsZ monomers, resulting in breakdown of the Z ring (9). The observed FtsZ-GFP patches and filaments are likely FtsZ polymers that disassemble before they can organize into a ring.We confirmed this result by overproducing SulA in wild-type cells and detecting FtsZ localization by IF (Fig. 2, C, D, and D1). The overall fluorescence patterns in cells producing FtsZ-GFP versus cells producing only native FtsZ were similar (Fig. 2, B1 and D1), although we observed fewer filaments with IF, perhaps because FtsZ-GFP confers slight resistance to SulA, or because the increased amount of FtsZ in FtsZ-GFP producing cells might titrate the SulA more effectively.Additionally, we wanted to observe the localization patterns of the membrane tethers FtsA and ZipA. Inasmuch as both proteins bind to the same C-terminal conserved tail of FtsZ (12–14), they would be expected to colocalize with the circumferential FtsZ patches in the Z ring. We visualized FtsA using protein fusions to mCherry and GFP (data not shown) as well as IF using a wild-type strain (WM1074) (Fig. 3 A). We found that the patchy ring pattern of FtsA localization was similar to the FtsZ pattern. ZipA also displayed a similar patchy localization in WM1074 by IF (Fig. 3 B).Open in a separate windowFigure 3Localization of FtsA (A) and ZipA (B) by IF using AlexaFluor 488. (C) FtsA-GFP ring. (D) Same cell shown in panel C with ZipA labeled with DyLight 550. (C1 and D1) Three-dimensional surface intensity plots of FtsA ring from panel C or ZipA ring from panel D, respectively. (E) Merged image of FtsA (green) and ZipA (red) from the ring shown in panels C and D. (F) Intensity plot of FtsA (green) and ZipA (red) of ring shown in panel E. The plot represents intensity across a line drawn counterclockwise from the top of the ring around the circumference, then into its lumen. Red/green intensity plot and three-dimensional surface intensity plots were created using the software ImageJ (19). Scale bar, 1 μm.To determine whether FtsA and ZipA colocalized to these patches, we used a strain producing FtsA-GFP (WM4679) for IF staining of ZipA using a red secondary antibody. FtsA-GFP (Fig. 3 C) and ZipA (Fig. 3 D) had similar patterns of fluorescence, although the three-dimensional intensity profiles (Fig. 3, C1 and D1) reveal slight differences in intensity that are also visible in a merged image (Fig. 3 E). Quantitation of fluorescence intensities around the circumference of the rings revealed that FtsA and ZipA colocalized almost completely in approximately half of the rings analyzed (Fig. 3 F, and see Fig. S2 A), whereas in the other rings there were significant differences in localization in one or more areas (see Fig. S2 B). FtsA and ZipA bind to the same C-terminal peptide of FtsZ and may compete for binding. Cooperative self-assembly of FtsA or ZipA might result in large-scale differential localization visible by 3D-SIM.In conclusion, our 3D-SIM analysis shows that the patchy localization of FtsZ is conserved in E. coli and suggests that it may be widespread among bacteria. After disassembly of the Z ring either in dividing cells or by excess levels of the cell division inhibitor SulA, FtsZ persisted as patches and short filamentous structures. This is consistent with a highly dynamic population of FtsZ monomers and oligomers outside the ring, originally observed as mobile helices in E. coli by conventional fluorescence microscopy (10) and by photoactivation single-molecule tracking (15). FtsA and ZipA, which bind to the same segment of FtsZ and tether it to the cytoplasmic membrane, usually display a similar localization pattern to FtsZ and each other, although in addition to the differences we detect by 3D-SIM, there are also likely differences that are beyond its ∼100-nm resolution limit in the X,Y plane.As proposed previously (16), gaps between FtsZ patches may be needed to accommodate a switch from a sparse Z ring to a more condensed ring, which would provide force to drive ring constriction (17). If this model is correct, the gaps should close upon ring constriction, although this may be beyond the resolution of 3D-SIM in constricted rings. Another role for patches could be to force molecular crowding of low-abundance septum synthesis proteins such as FtsI, which depend on FtsZ/FtsA/ZipA for their recruitment, into a few mobile supercomplexes.How are FtsZ polymers organized within the Z-ring patches? Recent polarized fluorescence data suggest that FtsZ polymers are oriented both axially and circumferentially within the Z ring in E. coli (18). The seemingly random orientation of the non-ring FtsZ polymeric structures we observe here supports the idea that there is no strong constraint requiring FtsZ oligomers to follow a circumferential path around the cell cylinder. The patches of FtsZ in the unperturbed E. coli Z ring likely represent randomly oriented clusters of FtsZ filaments that are associated with ZipA, FtsA, and essential septum synthesis proteins. New super-resolution microscopy methods should continue to shed light on the in vivo organization of these protein assemblies.     

Focus Issue on Roots: Branching Out in Roots: Uncovering Form,Function, and Regulation

Root branching is critical for plants to secure anchorage and ensure the supply of water, minerals, and nutrients. To date, research on root branching has focused on lateral root development in young seedlings. However, many other programs of postembryonic root organogenesis exist in angiosperms. In cereal crops, the majority of the mature root system is composed of several classes of adventitious roots that include crown roots and brace roots. In this Update, we initially describe the diversity of postembryonic root forms. Next, we review recent advances in our understanding of the genes, signals, and mechanisms regulating lateral root and adventitious root branching in the plant models Arabidopsis (Arabidopsis thaliana), maize (Zea mays), and rice (Oryza sativa). While many common signals, regulatory components, and mechanisms have been identified that control the initiation, morphogenesis, and emergence of new lateral and adventitious root organs, much more remains to be done. We conclude by discussing the challenges and opportunities facing root branching research.Branching through lateral and adventitious root formation represents an important element of the adaptability of the root system to its environment. Both are regulated by nutrient and hormonal signals (Bellini et al., 2014; Giehl and von Wirén, 2014), which act locally to induce or inhibit root branching. The net effect of these adaptive responses is to increase the surface area of the plant root system in the most important region of the soil matrix for resource capture (e.g. surface layers for phosphorus uptake and deeper layers for nitrate uptake) or to secure anchorage. Different species use different combinations of lateral or adventitious roots to achieve this, with lateral roots dominating the root system of eudicots while adventitious (crown and brace) roots dominate the root system of monocots, including in cereal crops.Our understanding of the mechanisms controlling lateral and adventitious root development has accelerated in recent years, primarily through research on model plants. The simple anatomy and the wealth of genetic resources in Arabidopsis (Arabidopsis thaliana) have greatly aided embryonic and postembryonic root developmental studies (De Smet et al., 2007; Péret et al., 2009a; Fig. 1, A and E). Nevertheless, impressive recent progress has been made studying root branching in other crop species, notably cereals such as maize (Zea mays) and rice (Oryza sativa).Open in a separate windowFigure 1.A to D, Schematics showing diversity in root system architecture at both seedling (left) and mature (right) stages in eudicots (A and C) and monocots (B and D). A, Arabidopsis root system. B, Maize root system. C, Tomato root system (for clarity, stem-derived adventitious roots are only shown in the labeled region). D, Wheat root system. E and F, Cross sections of emerging lateral root primordia in Arabidopsis (E) and rice (F). E and F are adapted from Péret et al. (2009b).In this Update, we initially describe the diversity of postembryonic root forms in eudicots and monocots (Fig. 1). Next, we highlight recent advances in our understanding of the genes, signals, and mechanisms regulating lateral root and adventitious root branching in Arabidopsis, rice, and maize. Due to space limits, we cannot provide an exhaustive review of this subject area, focusing instead on recent research advances. However, we direct readers to several recent in-depth reviews on lateral root (Lavenus et al., 2013; Orman-Ligeza et al., 2013) and adventitious root development (Bellini et al., 2014).     

To avoid a mating mishap,yeast focus and communicate

During mating, yeast cells must perforate their rigid cell walls at the right place to allow cell–cell fusion. In this issue, Dudin et al. (2015; J. Cell Biol. http://dx.doi.org/jcb.201411124) image mating fission yeast cells with unprecedented spatiotemporal resolution. The authors find that when mating cells come into contact, they form aster-like actin structures that direct cell wall remodeling precisely to the point of contact.At its core, sex is about the fusion of two haploid cells to form a diploid. For nonmotile cells like yeasts, that requires growth of mating projections to bridge the distance between the mating partners (Fig. 1 A). Yeast cells are protected from osmotic lysis by rigid cell walls, and growth of the mating projection involves local secretion of hydrolases that make the cell wall more elastic at the growing tip (Klis et al., 2006). As the wall expands, new components are added by synthases to maintain a continuous, unbroken wall. The process is orchestrated by a “cell wall integrity” signaling pathway, which monitors cell wall stress and delicately balances hydrolysis and synthesis to guarantee that no holes develop (Levin, 2011). But when it comes to mating, a hole must be made in both partners’ walls at the point of contact to allow cell–cell fusion. Precise positioning is key, as an off-center hole would lead to lysis. How is such precision achieved?Open in a separate windowFigure 1.Cell fusion during yeast mating: focus and communication. (A) Mating fission yeast cells grow projections toward each other and fuse at the point of contact. (B, left) Secreted hydrolases weaken the rigid cell wall to enable expansion, and rapidly diffuse away. (B, right) At a point of cell–cell contact, diffusional escape paths are longer, so hydrolases build up. (C) Focused delivery of secretory vesicles (ves) in mating budding yeast after contact. The image is adapted from Gammie et al. (1998), © The American Society for Cell Biology. (D) Actin cables during growth of the projection (left) and in the fusion focus (right). (E) Distribution of hydrolases and synthases in fusing cells. (F) The fusion focus forms first in the h⁻ mating partner and then in the h⁺ mating partner. CW, cell wall; PM, plasma membrane; N, nucleus; V, vacuole.An appealingly simple hypothesis—based on the observation that many hydrolases are secreted enzymes that can only transiently degrade the wall before diffusing away (Fig. 1 B)—is that when the mating projections come into contact, hydrolases from one partner would diffuse into the local wall of the other. Because diffusional escape paths are longer when cells are juxtaposed, hydrolases would be concentrated and make a hole only at the point of contact (Huberman and Murray, 2014). However, this purely geometrical effect cannot be the whole story, as classic genetic studies identified mutants of Saccharomyces cerevisiae that grew mating projections and achieved cell wall contact but failed to degrade the cell wall between mating partners (Kurihara et al., 1994). One set of mutants revealed that fusion requires especially high levels of pheromone secretion, which suggests that mating partners signal to each other to coordinate local wall remodeling (Brizzio et al., 1996). Elegant cytological analyses of another set of mutants have also suggested that vesicles delivering hydrolases are targeted precisely to the site of cell–cell contact (Fig. 1 C; Gammie et al., 1998). These inferences are strongly supported and expanded by a study in this issue (Dudin et al.), which provides a beautifully detailed characterization of mating in the distantly related fission yeast Schizosaccharomyces pombe.Using time-lapse microscopy and super-resolution imaging to monitor components of the actin cytoskeleton, Dudin et al. (2015) found that actin cables directed myosin V traffic to a broad zone at the tip of the growing mating projection. However, after cell–cell contact, actin cables were tightly focused toward a central “fusion focus” (Fig. 1 D). After focus formation, hydrolases were concentrated in a narrow region, whereas synthases were still distributed broadly (Fig. 1 E). The authors suggest that tightly focused myosin V–mediated delivery of hydrolases overwhelms the local synthases to make a hole in the central cell wall. In the surrounding wall, synthases counteract hydrolases to maintain cell wall integrity.How does the fusion focus form? A mating-specific formin, Fus1, became tightly localized to a small spot, where it presumably promoted focused actin polymerization and barbed-end anchoring (Dudin et al., 2015). Focus formation could arise from highly focused upstream signaling by formin regulators like Cdc42. Another possibility is suggested by the observation that, as also seen in budding yeast (Sheltzer and Rose, 2009), myosin V was required for focus formation. Thus, one could envision a positive feedback focusing mechanism in which formin-nucleated actin cables enable myosin V–mediated delivery of formins or their activators. Cells in which fusion focus formation was blocked by mutation of Fus1 or myosin V were unable to degrade juxtaposed cell walls and kept growing longer projections, attesting to the importance of the focus in enabling cell wall degradation.Why does the fusion focus only form upon cell–cell contact? The walls of the mating projections display mating type–specific agglutinins, which help mating partners stick to each other and might conceivably signal that contact has been established. Alternatively, focus formation might be triggered upon perception of a high-threshold pheromone concentration (Brizzio et al., 1996): pheromone levels would rise as the projections approach each other, and might be further increased after contact due to the same geometrical considerations discussed earlier for hydrolases.Intriguingly, Dudin et al. (2015) found that one of the mating partners, the h⁻ cell, always developed an actin fusion focus before the other, the h⁺ cell (Fig. 1 F). The basis for this asynchrony is unknown, but if the focus is indeed triggered by a threshold pheromone level, it could be that one pheromone crosses the threshold before the other. The h⁻ cells produce M-factor, whereas h+ cells produce P-factor. If P-factor were to accumulate more rapidly at the contact site, it might reach critical levels and trigger h⁻ cells to make their focus first. The ensuing more focused secretion of M-factor by the h⁻ cell might then trigger and correctly position focus formation by the h⁺ cell. Whatever the mechanism, the finding that one partner always focuses first makes it attractive to speculate that this asynchrony enables communication between mating partners that allows them to coordinate focus formation directly across from each other.     

The quest for spatio-temporal control of CAR T cells

Chimeric antigen receptors (CARs) are synthetic receptors capable of directing potent antigen-specific anti-tumor T cell responses. A recent report by Wu et al. extends a series of strategies aiming to curb excessive T cell activity, utilizing in this instance a chemical dimerizer to aggregate antigen-binding, T cell-activating and costimulatory domains.Chimeric antigen receptor (CAR) therapy relies on T cell engineering to generate tumor-targeted T cells with enhanced anti-tumor functions¹. CAR therapy has so far achieved its most remarkable clinical successes against CD19-positive hematological malignancies and is now on the verge of being developed for solid tumors². Two safety concerns have, however, emerged from the CD19 experience, which should be addressed for CAR therapy to be broadly applicable. One is the eventual on-target/off-tumor effect of CAR T cells on normal tissues. Even though this concern may be mitigated in the case of CD19 CAR T cell-induced B cell aplasia, strategies designed to reduce or prevent its potential occurrence with other targets are needed². The other concern is a severe cytokine release syndrome (CRS), arising from large-scale synchronized T cell activation upon engaging the target antigen in some CAR T cell recipients².Several innovative strategies have been recently proposed to address these safety concerns. These strategies make use of remote or cell autonomous controls (Figure 1), utilizing small molecules, antibodies or synthetic receptors to regulate T cell activity. One approach is to activate a latent suicide switch, such as the inducible caspase-9 (iCasp9) enzyme, through the administration of a small molecule to induce T cell apoptosis³ (Figure 1a). Bifunctional small molecules that mediate the binding between antigen and CAR have also been developed to regulate target engagement⁴ (Figure 1b). A variation on this approach uses antibodies to mediate antigen recognition on target cells and binding of T cells expressing a synthetic Fc receptor⁵ (Figure 1b). These designs enable remote temporal control of T cell activity but do not provide a means to enhance tumor selectivity of the CAR T cells. To this end, combinatorial approaches integrating two autonomous antigen inputs to control CAR T cell functions have been developed to spatially discriminate between normal and tumor cells expressing a common target. One such approach utilizes synthetic inhibitory receptors, termed iCARs, which are derived from the PD-1 or CTLA-4 receptors, to protect normal cells based on the iCAR''s recognition of an antigen present on the normal cells but not the tumor cells⁶ (Figure 1c). Another approach utilizes complementary signals split between two receptors — a CAR for T cell activation and a chimeric costimulatory receptor (CCR) providing costimulation — such that they are both expressed by the tumor cells but found alone on normal cells⁷ (Figure 1d). Acting in cell autonomous fashion, the required co-engagement of the CCR and the CAR upon recognition of two independent antigens reinforces tumor selectivity in vivo⁷.Open in a separate windowFigure 1Building controls into engineered T cells. (a) The small molecule AP1903 can dimerize the suicide switch iCasp9 to induce T cell apoptosis. (b) Bifunctional small molecule bridging the binding between antigen and CAR or antibody mediating the interaction between antigen and synthetic Fc receptor can be remote controls of CAR T cells. (c) iCAR can inhibit CAR function in the presence of an antigen present in normal cells but not tumor cells. (d) CCR binding to a second antigen in tumor cells is required for full T cell activation. (e) The small molecule AP21976 can dimerize two independent signaling entities through an FKBP-FRB module to control T cell activation. (a, b, e) Strategies employing one remote control (antibody or small molecule) in addition to one autonomous control (antigen A). (c, d) Strategies with two autonomous controls (antigen A and antigen B). Negative regulation involves inducing apoptosis (a) or turning off T cell activation (c) by input 2 while positive regulation (b, d, e) results in T cell activation by input 2.In a recent paper published in Science, Wu et al.⁸ showed a novel design incorporating a remote control of CAR T cells, whereby a small molecule is used to dimerize antigen-binding and signaling domains (Figure 1e). At variance with the small molecule-controlled suicide switch, this ON-switch design represents a positive reversible regulation, as it does not eliminate T cells but rather restricts their activities. The remote control takes advantage of well-established chemically induced dimerization (CID) modules developed in the 1990s, where two proteins bind only in the presence of a third chemical, such as a small molecule⁹. One such widely used CID module is the FKBP and FRB_T2098L that heterodimerize in the presence of rapamycin or its less immunosuppressive analog AP21976. The receptor for antigen and a dual-signaling, costimulatory and activating domain analogous to that of a second generation CAR, were independently fused to FKBP and FRB_T2098L so that AP21976-induced FKBP and FRB_T2098L dimerization could aggregate these entities (Figure 1e). This design controls intracellular assembly of a signaling complex without affecting the antigen binding properties as afforded by the bifunctional small molecules or antibodies at the interface of T cells and target cells (Figure 1b). After screening various domain configurations in leukemic Jurkat cells with AP21976-dependent NFAT activation and IL-2 production assays, a design that worked with both the FKBP-FRB_T2098L and the gibberellin-induced GID1-GAI heterodimerization modules was identified. Single molecule imaging of ON-switch CAR assembly in Jurkat cells showed that two molecular parts are equally constrained to immobilized antigens only in the presence of AP21976. Subsequent characterization of the ON-switch CAR in primary human CD4⁺ T cells showed that both AP21976 and antigen are required for the induction of CD69 expression, a biomarker of T cell activation, the secretion of both IL-2 and IFNγ, and the proliferation of CD4⁺ cells. Most gratifyingly, there was a positive correlation between these responses and the AP21976 dosage, suggesting the possibility of achieving titratable control of T cells. Human primary CD8⁺ T cells with ON-switch CAR in three different cytotoxicity assays also demonstrated antigen- and AP21976-dependent killing of tumor cells, which was also titratable by AP21976. The killing ability of ON-switch CAR CD8⁺ T cells was reversible, as removal of AP21976 abrogated tumor cell lysis.Wu et al. proceeded to explore in vivo activity in a mouse xenograft model. Due to the short plasma half-life and the high cost of AP21976, the study is limited to a very short-term protocol of 39 h. Tumor cells were injected into the peritoneal cavity 14 h prior to the injection of the engineered T cells. Four injections of AP21976 in the subsequent 25 h were required to induce anti-tumor activity in this intraperitoneal cytotoxicity assay. Further investigations with a more relevant protocol allowing for tumor engraftment and longer term follow-up of T cell effectiveness will be needed to establish whether AP21976 can remotely control ON-switch CAR T cells to reject a tumor.Wu and coauthors have thus engineered a novel ON-switch CAR design and demonstrated titratable, reversible and antigen-dependent T cell functions controlled by a dimerizing small molecule. Another group is also conducting preclinical studies exploring a variant small molecule-controlled CAR design for solid tumor rejection¹⁰. However, there are still challenges to address before future clinical applications. The authors pointed out the need to develop controller chemicals that have clinically optimized pharmacokinetic properties, as the half-life of AP21976 is short and impractical for clinical application. Thus, how many injections per day, for how many weeks or months, would be required to achieve tumor rejection? Another unresolved question is whether a small molecule with optimal pharmacokinetic properties could effectively curb CRS and off-tumor reactivity. Overall, this elegant study provides valuable insights for further refining spatio-temporal control of cell therapy and applying it to CAR T cell technology.     

Silent Genes: Antimicrobial Resistance and Antibiotic Production

Silent genes are DNA sequences that are generally not expressed or expressed at a very low level. These genes become active as a result of mutation, recombination, or insertion. Silent genes can also be activated in laboratory conditions using pleiotropic, targeted genome-wide, or biosynthetic gene cluster approaches. Like every other gene, silent genes can spread through horizontal gene transfer. Most studies have focused on strains with phenotypic resistance, which is the most common subject. However, to fully understand the mechanism behind the spreading of antibiotic resistance, it is reasonable to study the whole resistome, including silent genes. Open in a separate window     

Bringing Rad52 foci into focus

In 2007, we published the results of a genome-wide screen for ORFs that affect the frequency of Rad52 foci in yeast. That paper was published within the constraints of conventional online publishing tools, and it provided only a glimpse into the actual screen data. New tools in the JCB DataViewer now show how these data can—and should—be shared.

Complete screen data

https://doi.org/10.1083/jcb.201108095.dv The Rad52 protein has pivotal functions in double strand break repair and homologous recombination. The activity of Rad52 is often monitored by the subnuclear foci that it forms spontaneously in S phase or after DNA damage (Lisby et al., 2001). In mammals, the functions of yeast Rad52 may be divided between human RAD52 and the tumor suppressor BRCA2 (Feng et al., 2011). The full host of molecular players that govern Rad52 focus formation and maintenance was not well known when we initiated our screen. Using a high-content, image-based assay, we assessed the proportion of cells containing spontaneous Rad52-YFP foci in 4,805 viable Saccharomyces cerevisiae deletion strains (Alvaro et al., 2007). Starting with 96-well arrays of a deletion strain library, we created hybrid diploid strains (homozygous for the deletions) using systematic hybrid loss of heterozygosity (SHyLOH; Alvaro et al., 2006). We then manually and sequentially examined each strain using epifluorescence microscopy for the presence of Rad52-YFP foci. All of our image analysis was performed manually.As is often the case, our screen was published showing only a couple of representative images and providing data tables to summarize the findings. Tomes of data that could not be included in the published paper were relegated to supplemental Excel tables, typical of genome-wide screens. Also, the raw image data were sequestered in the laboratory on DVDs. With considerable help from JCB and Glencoe Software, we are delighted that the raw data from our Rad52 screen are now freely available online through the JCB DataViewer. A new interface within the JCB DataViewer brings presentation and preservation of high-content, multidimensional image-based screening data to a whole new level. To facilitate the development of this new interface, JCB required a dataset that was not time sensitive, and we were happy to provide our previously published Rad52 data. In the future, this new interface will be used to present high-content screening (HCS) datasets linked to published JCB papers. Indeed, the first publication of this sort appears in this issue of JCB (Rohn et al., 2011).The presentation of our data in the JCB DataViewer clearly shows the many benefits of this new publishing resource for the scientific community. Users now can view the complete collection of 3D image data across the entire screen, not just the two images in our original publication (Alvaro et al., 2007). Additionally, detailed information on image acquisition parameters, locus identities, and more is easily accessible (Fig. 1). Phenotypic scoring results can be visualized in interactive chart formats (Fig. 1), and search (Fig. 2) and database-linking tools (Fig. 1) allow extensive mining of the data for genes and phenotypes of interest. These tools provide an unprecedented view into HCS data in their entirety, as well as a means for authors to share and archive their data. This kind of accessibility to the direct visualization of the entire set of original screening data, on a scale previously only available to the scientists performing the screen, allows users to understand the full context of the image data analyzed in a screen. Furthermore, it is only through full access to the raw images and associated metadata that this information can be of maximum use to the community for large-scale data mining.Open in a separate windowFigure 1.The HCS interface of the JCB DataViewer provides interactive tools for the analysis of complete datasets from image-based screens. The miniviewer (top left) provides information for each gene in the screen through a zoomable and scrollable display of original multidimensional image data. It contains detailed metadata and a gene ontology (GO) summary, a link to a relevant external database (e.g., the Saccharomyces Genome Database [SGD]; top right), and a link to phenotypic scoring data for the complete screen in the chart view (bottom right). Within the chart view, hits designated by the screen authors are shown in blue, and the strain currently on display in the miniviewer is shown in red. The plate view (bottom left) shows the position of the strain of interest (red box) relative to other strains screened.Open in a separate windowFigure 2.The HCS interface of the JCB DataViewer provides search tools for the mining of complete datasets from image-based screens. (A) Users can search screen data by gene name or keywords (e.g., DNA repair). (B) Users can pick candidates for further analysis from the phenotypic scoring information in the chart view.As in all large-scale screens, the real data are variable; e.g., some strains provide a clear Rad52 focus phenotype, whereas others are more ambiguous. For our particular screen, images were not collected using automated technology but were acquired manually, strain by strain, over a period of months, leading to different levels of fluorescence intensity of Rad52-YFP as a result of, for example, changes in the intensity of our mercury arc lamp. Differences also exist in the number of fields and z stacks captured for each strain. In the absence of automated image collection, images from the primary screen in a few cases were not archived with the others and thus for all intents and purposes have been lost. In addition, our Rad52 screen only assayed nonessential genes, and some mutants are refractory to the SHyLOH methodology. Knowing all of this information allows users to view the data in a realistic manner and further highlights the importance of providing a central repository to archive HCS data.When published through conventional publication media, many important imaging details are known only to the original screeners. The new HCS interface of the JCB DataViewer shines a light on screening data as metadata become freely accessible, allowing any user to ask novel questions of the dataset. For example, the plate view for images (Fig. 1) allows users to assess whether neighboring colonies played any role in determining the phenotype and to delve deeper into why that might be. For example, are any “hits” a result of contamination from adjacent strains, resulting in clusters of positives? In the context of an automated screen, how were control and experimental samples arrayed across a plate during data collection? Did the controls on a particular plate behave as expected? Because our screen used a novel chromosome-specific loss of the heterozygosity method, users can ask whether mutations on specific chromosomes share features of Rad52 foci levels. The global resolution of the dataset provided through this new interface puts users of the dataset as close to the seat of the original screening scientist as possible, allowing them to ask, “what did the authors really see?”Presenting HCS data in the JCB DataViewer holds immense potential value to the scientific community. Through this new interface, users can access powerful interactive tools for analyzing scored phenotypes across the entire dataset (Fig. 1). Each gene ID can be charted against the phenotypic parameters scored in the original screen (e.g., the percentage of cells with Rad52 foci) and compared with all other loci (Fig. 1). Users can take our data and create their own list of hits based on their criteria, create a gallery of thumbnails for their selections (Fig. 2), and seamlessly move between their list of hits and the original data in the plate display format (Fig. 1). Users can also compare their candidates with our list (Fig. 2). The ability to visualize these data for comparative analyses creates a whole new perspective. The HCS interface of the JCB DataViewer allows users to look for their favorite gene, compare related genes, and discover new genes they never anticipated were involved in a given process.In summary, these new features of the JCB DataViewer will allow users to access the primary data from large-scale screens and to look at the full dataset to see what all of the images really look like. The ability to mine these data opens up whole new dimensions in data sharing and transparency. In the future, we anticipate that it will be possible to search many genome-wide screens, such as our Rad52 dataset, to identify commonalities in protein localization, concentration, cell morphology, etc. However, this will only occur if image data are archived and made freely available to the scientific community. We wholeheartedly support the efforts of JCB and hope that groups that use image-based HCS will increasingly make their images available using tools such as the JCB DataViewer.     

Nanoscale Distribution of Ryanodine Receptors and Caveolin-3 in Mouse Ventricular Myocytes: Dilation of T-Tubules near Junctions

We conducted super-resolution light microscopy (LM) imaging of the distribution of ryanodine receptors (RyRs) and caveolin-3 (CAV3) in mouse ventricular myocytes. Quantitative analysis of data at the surface sarcolemma showed that 4.8% of RyR labeling colocalized with CAV3 whereas 3.5% of CAV3 was in areas with RyR labeling. These values increased to 9.2 and 9.0%, respectively, in the interior of myocytes where CAV3 was widely expressed in the t-system but reduced in regions associated with junctional couplings. Electron microscopic (EM) tomography independently showed only few couplings with caveolae and little evidence for caveolar shapes on the t-system. Unexpectedly, both super-resolution LM and three-dimensional EM data (including serial block-face scanning EM) revealed significant increases in local t-system diameters in many regions associated with junctions. We suggest that this regional specialization helps reduce ionic accumulation and depletion in t-system lumen during excitation-contraction coupling to ensure effective local Ca²⁺ release. Our data demonstrate that super-resolution LM and volume EM techniques complementarily enhance information on subcellular structure at the nanoscale.The contraction of cardiac ventricular myocytes depends on the rapid cell-wide transient increase in intracellular [Ca²⁺] upon depolarization of the cell-membrane potential. The cardiac ryanodine receptor (RyR) (1), which is the intracellular Ca²⁺ release channel in the sarcoplasmic reticulum (SR), plays a central role in shaping Ca²⁺ transients. RyRs form clusters of various sizes (2,3) with the majority located within junctions between the SR and the surface membrane and its cytoplasmic extension, the transverse tubular (t-) system. It has been suggested that some RyR clusters are associated with caveolae, a specialized signaling microdomain of the surface membrane. Previous studies were complicated by the limited resolution of optical imaging methods of ∼250 nm, much larger than the nanometer scale of RyRs and caveolae. Accordingly, these studies report varying colocalization between RyRs and caveolin-3 (CAV3), a caveolar marker also expressed in the t-system (4,5).In this work, we investigated the relative distribution of CAV3 and RyRs in mouse ventricular myocytes both in the cytosol and near the cell surface with super-resolution fluorescence microscopy that achieves a resolution approaching 30 nm. Our data revealed unexpected local t-system swellings near junctional couplings, which was supported by two different three-dimensional electron microscopy (EM) modalities with <10-nm resolution: EM tomography and serial block-face scanning EM (SBFSEM).Super-resolution images of CAV3 and RyR labeling at the surface sarcolemma of mouse myocytes showed little overlap, suggesting that few RyRs were in couplings with caveolae (Fig. 1 A, for detailed methods, see the Supporting Material). Only ∼4.8% of RyR labeling was associated with CAV3 positive areas and ∼3.5% of CAV3 associated with RyR positive areas (n = 6 cells from three animals, Fig. 1 B, see also Table S1 in the Supporting Material), broadly consistent with previous data in rats (6). To support this finding, EM tomography was applied to mouse ventricular tissue that included a part of the surface sarcolemma, to our knowledge for the first time. Segmentation of peripheral couplings (containing RyR foot structures) and surface caveolae (∼60 nm in diameter and often interconnected) confirmed that the great majority of peripheral couplings were in regions devoid of caveolae (Fig. 1 C). A few junctional couplings containing feet were between caveolae and subsarcolemmal SR (Fig. 1 D, see also Fig. S1 and Movie S1 in the Supporting Material). We conducted a similar analysis in the cytosol where CAV3 expression occurs in the t-system (5) and RyRs are abundant in dyadic junctions between the t-system and SR terminal cisterns.Open in a separate windowFigure 1Colocalization of CAV3 and RyRs at the surface sarcolemma. (A) Super-resolution micrograph of the distribution of CAV3 (green) and RyRs (red) at the surface of a mouse cardiac myocyte. (B) Analysis of the association of CAV3 with RyRs. The fraction of RyR labeling within CAV3 positive areas was ∼4.8% (front data) whereas ∼3.5% of CAV3 was found in RyR-positive membrane areas. (C) Segmented EM tomogram containing a patch of surface sarcolemma (light blue) and associated caveolae (green) as well as peripheral couplings (red). (D) Detailed view of a region with abundant caveolae. (Arrows) Couplings with caveolae.As shown in Fig. 2 A, the spatial distribution of CAV3 and RyR clusters in super-resolution micrographs taken several microns below the surface sarcolemma is consistent with this view. The association of the two labels is slightly increased (as compared to the surface), according to distance analysis with 9% of CAV3 and 9.2% of RyR labeling associating with each other (Fig. 2 B, n = 6 cells from three animals). The similarity of manually traced t-system in EM tomograms (Fig. 2 C) and super-resolved CAV3 labeling suggested that CAV3 is widely distributed in the t-system except for regions where dyadic membrane junctions occur as CAV3 labeling was much weaker in regions with strong RyR labeling. It was notable that the t-system diameter appeared to increase at regions of strong RyR labeling (Fig. 2 D), broadly consistent with the behavior seen in tomograms (Fig. 2 C). This was confirmed by a quantitative analysis of t-tubule diameters in dyadic versus extradyadic regions on the basis of CAV3 and RyR labeling, with full-width at quarter-maximum mean diameters increasing from ∼150 nm distal to dyads, to ∼190 nm (using CAV3 signal only) or ∼280 nm (using CAV3 and RyR signal) near dyads (Fig. 2, G and H, see also Methods in the Supporting Material). The combined RyR and CAV3 signals seemed to be a better representation of the entire t-system lumen near junctions (see Fig. S2).Open in a separate windowFigure 2Distribution of CAV3 and RyRs in the cell interior. (A) Super-resolution micrograph of CAV3 (green) and RyR (red) distribution at t-system. (Arrow) Direction of longitudinal cell axis. (B) Distance analysis of the CAV3 and RyR association (N = 6 cells per group). (C) Segmented EM tomogram of a similar region with three-dimensional mesh models of t-system membrane (green) and dyadic couplings (red). (D) This image illustrates the tracing (white path) of t-tubules. The label distribution was extracted and linearized along the path (E) to calculate a mask that shows the full width at quarter-maximum diameter along tubules, CAV3 (green) and RyR (red) (F). (G) Histograms of local diameters extracted from traced t-tubules. (H) Mean diameters in junctional (dyad) and nonjunctional (ex-dyad) regions. See main text and the Supporting Material for details. ^**p < 0.01.Taken together, super-resolution imaging and EM tomography strongly support the presence of local t-system dilations in regions where the t-system opposes SR at dyads and such t-system bulges are connected by narrower tubule segments. Further support was provided by SBFSEM, another volume EM technique to study larger cell volumes (albeit at the expense of a slightly lower resolution). SBFSEM clearly showed local t-system dilations were regularly involved in the architecture of most (but not all) dyads (Fig. 3, see also Fig. S3 and Movie S2), as also observed in full three-dimensional super-resolution images (see Fig. S3 C).Open in a separate windowFigure 3Segmented SBFSEM data showing t-system dilations near dyadic junctions. (A) The overview shows t-system membranes (green) and jSR (red) in a mouse myocyte. (B, enlarged inset from panel A) Thin connecting tubules (arrows) and regular swellings in junctional regions at z-lines.Our data identify local dilations of the t-system associated with dyads in mouse cardiac myocytes. Frequent tubule distensions had been observed especially at the intersections of transverse and axial tubules (7), and constrictions were seen in rabbit myocytes although their relationship to dyads was unknown (8). The increased local t-system lumen near junctions may help reduce the predicted ionic accumulation/depletion during excitation-contraction coupling (9). Alternatively, it might simply be secondary to increasing local membrane area and allow the formation of large area junctions that harbor many RyRs. In connection with this point, it would be interesting to investigate the t-system near junctions in species that have larger average tubule diameters (e.g., human and rabbit (10)), or if this architecture changes in mouse heart failure models where t-tubule diameters are often increased.Most peripheral couplings were in regions void of surface caveolae, although a small number of RyR clusters were in junctional couplings between subsarcolemmal SR and caveolae as shown both by the low colocalization between CAV3 and RyRs as well as direct evidence from EM tomography. Similarly, a relatively small fraction of CAV3 colocalized with RyR clusters in the t-system although CAV3 was expressed widely in the t-system. A structural role of CAV3 in the t-system is still unclear—t-tubules in tomogram data did not reveal distinct caveolae shapes on the t-system membrane (see Fig. S4), although this might change in pathology (11). In any case, the t-system exhibits high curvature orthogonal to the tubule axis, which may be supported by CAV3 oligomerization. In addition, the presence of CAV3 in the t-system may be important for regulating other signaling systems (e.g., adrenergic signaling).Finally, our data demonstrate that complementary data from optical super-resolution and three-dimensional EM images assists data interpretation and reliability. We suggest that truly correlative optical and EM imaging approaches should provide further information and improve our knowledge of the basis of cardiac excitation-contraction coupling.